Thanks for visiting The Cell Phone Junkie! I will be taking the time each week to discuss my favorite topic, cell phones. Any feedback is appreciated and welcome. You can email me at: questions (AT) thecellphonejunkie (DOT) com or call: 206-203-3734 Thanks and welcome!
…
continue reading
内容由PyTorch, Edward Yang, and Team PyTorch提供。所有播客内容(包括剧集、图形和播客描述)均由 PyTorch, Edward Yang, and Team PyTorch 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal。
Player FM -播客应用
使用Player FM应用程序离线!
使用Player FM应用程序离线!
Anatomy of a domain library
Manage episode 295783831 series 2921809
内容由PyTorch, Edward Yang, and Team PyTorch提供。所有播客内容(包括剧集、图形和播客描述)均由 PyTorch, Edward Yang, and Team PyTorch 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal。
What's a domain library? Why do they exist? What do they do for you? What should you know about developing in PyTorch main library versus in a domain library? How coupled are they with PyTorch as a whole? What's cool about working on domain libraries?
Further reading.
- The classic trio of domain libraries is https://pytorch.org/audio/stable/index.html https://pytorch.org/text/stable/index.html and https://pytorch.org/vision/stable/index.html
Line notes.
- why do domain libraries exist? lots of domains specific gadgets,
inappropriate for PyTorch - what does a domain library do
- operator implementations (old days: pure python, not anymore)
- with autograd support and cuda acceleration
- esp encoding/decoding, e.g., for domain file formats
- torchbind for custom objects
- takes care of getting the dependencies for you
- esp transformations, e.g., for data augmentation
- models, esp pretrained weights
- datasets
- reference scripts
- full wheel/conda packaging like pytorch
- mobile compatibility
- operator implementations (old days: pure python, not anymore)
- separate repos: external contributors with direct access
- manual sync to fbcode; a lot easier to land code! less
motion so lower risk
- manual sync to fbcode; a lot easier to land code! less
- coupling with pytorch? CI typically runs on nightlies
- pytorch itself tests against torchvision, canary against
extensibility mechanisms - mostly not using internal tools (e.g., TensorIterator),
too unstable (this would be good to fix)
- pytorch itself tests against torchvision, canary against
- closer to research side of pytorch; francesco also part of papers
83集单集
Manage episode 295783831 series 2921809
内容由PyTorch, Edward Yang, and Team PyTorch提供。所有播客内容(包括剧集、图形和播客描述)均由 PyTorch, Edward Yang, and Team PyTorch 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal。
What's a domain library? Why do they exist? What do they do for you? What should you know about developing in PyTorch main library versus in a domain library? How coupled are they with PyTorch as a whole? What's cool about working on domain libraries?
Further reading.
- The classic trio of domain libraries is https://pytorch.org/audio/stable/index.html https://pytorch.org/text/stable/index.html and https://pytorch.org/vision/stable/index.html
Line notes.
- why do domain libraries exist? lots of domains specific gadgets,
inappropriate for PyTorch - what does a domain library do
- operator implementations (old days: pure python, not anymore)
- with autograd support and cuda acceleration
- esp encoding/decoding, e.g., for domain file formats
- torchbind for custom objects
- takes care of getting the dependencies for you
- esp transformations, e.g., for data augmentation
- models, esp pretrained weights
- datasets
- reference scripts
- full wheel/conda packaging like pytorch
- mobile compatibility
- operator implementations (old days: pure python, not anymore)
- separate repos: external contributors with direct access
- manual sync to fbcode; a lot easier to land code! less
motion so lower risk
- manual sync to fbcode; a lot easier to land code! less
- coupling with pytorch? CI typically runs on nightlies
- pytorch itself tests against torchvision, canary against
extensibility mechanisms - mostly not using internal tools (e.g., TensorIterator),
too unstable (this would be good to fix)
- pytorch itself tests against torchvision, canary against
- closer to research side of pytorch; francesco also part of papers
83集单集
Todos los episodios
×欢迎使用Player FM
Player FM正在网上搜索高质量的播客,以便您现在享受。它是最好的播客应用程序,适用于安卓、iPhone和网络。注册以跨设备同步订阅。